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Smart Human Identification System Based on PPG and ECG Signals in Wearable Devices

机译：可穿戴设备中PPG和ECG信号的智能人体识别系统

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摘要

In this paper, we propose a novel privacy-preserving identification-permission system (entitled Smart Human Identification System) to provide human identification, privacy, and security for users of wearables devices. To perform this function, we divided the system into six algorithms. We used PPG and ECG signals from two public datasets (MIMIC and CapnoBase). The proposed system creates a human ID and then compares it to other individuals and tests its accuracy to evaluate the quality of using biosignals for direct human identification in wearable devices. The experimental results indicate that the proposed system presented accuracy for the PPG signals from MIMIC and CapnoBase equal to 96.875% and 99.15%, respectively. For the ECG signals from MIMIC and CapnoBase, the accuracy obtained was 96.6% and 90.66%, respectively.
机译：在本文中，我们提出了一种新的隐私保留识别权限系统（题为智能人体识别系统），为可穿戴设备设备的用户提供人类的识别，隐私和安全性。 要执行此功能，我们将系统划分为六个算法。 我们使用来自两个公共数据集（模拟和Capnobase）的PPG和ECG信号。 所提出的系统创建了人体ID，然后将其与其他个人进行比较，并测试其准确性以评估使用生物功能的质量，以便在可穿戴设备中直接人体识别。 实验结果表明，所提出的系统分别呈现来自模拟物和冠诺酶的PPG信号的准确性，分别等于96.875％和99.15％。 对于来自模拟和载体碱基的ECG信号，所获得的准确度分别为96.6％和90.66％。

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